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Background subtraction examples
Subtract background shape evaluated in run 192
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from pyimgalgos.GlobalUtils import subtract_bkgd # once per run: sp.nda_peds = sp.det.pedestals(runnum) sp.nda_bkgd = sp.det.bkgd(runnum) # get n-d array with averaged background from calib/.../pixel_bkgd sp.nda_smask = sp.det.mask(evt, calib=False, status=True, edges=True, central=True, unbond=True, unbondnbrs=True) # windows for background normalization winds_bkgd = [(s, 10, 100, 270, 370) for s in (4,12,20,28)] # use part of segments 4,12,20,28 to subtr bkg # in the event loop nda_raw = sp.det.raw(evt) if nda_raw is not None : nda = np.array(nda_raw, dtype=np.float32, copy=True) nda -= sp.nda_peds # Subtract background shape averaged for pure water nda = subtract_bkgd(nda, sp.nda_bkgd, mask=sp.nda_smask, winds=sp.winds_bkgd, pbits=0) |
Subtract background shape evaluated in run 192
Radial background subtraction
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Background shape was evaluated WITH common mode correction. Central ; central 2x1s got offset due to non-uniform water background shape. |
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- masked pixels contributes to peak at 0
- 1-, 2- and 3- photon peaks are seen
- common mode correction before background subtraction does not work well in this data sample due to significant fraction of 1-photon peak next to noise peak, which makes an offset due to illumination.
- common mode correction after background subtraction does not work - it moves noise peak to 0 and destroys background subtraction results.
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Any Potentially any non-dark data spectra potentially can be used to calibrate pixel gain. |
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